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When glass absorbs high energy from ultrashort-pulsed lasers, a very rapid melting-cooling event occurs. Images taken by a Scanning Electron Microscope (SEM) reveal a surface feature which elucidates the glass is heated to above 2000 °C. A series of voids along the laser path is also observed and analyzed by SEM and High-angle Annular Dark-filed Scanning Transmission Electron Microscopy (HAADF-STEM). Molecular Dynamic simulation predicting observable voids in fused silica glass requires the temperature to be above 10,000 Kelvin. This suggests that the thermal effect from nonlinear absorption along cannot explain the void generation. Thermal stress analysis based on three different types of glasses revealed that stress generated by laser heating is highly correlated to thermal expansion coefficient. Such thermal stress may be a key factor for laser cutting.

High-precision segmentation of ancient mural images is the foundation of their digital virtual restoration. However, the complexity of the color appearance of ancient murals makes it difficult to achieve high-precision segmentation when using traditional algorithms directly. To address the current challenges in ancient mural image segmentation, an optimized method based on a superpixel algorithm is proposed in this study. First, the simple linear iterative clustering (SLIC) algorithm is applied to the input mural images to obtain superpixels. Then, the density-based spatial clustering of applications with noise (DBSCAN) algorithm is used to cluster the superpixels to obtain the initial clustered images. Subsequently, a series of optimized strategies, including (1) merging the small noise superpixels, (2) segmenting and merging the large noise superpixels, (3) merging initial clusters based on color similarity and positional adjacency to obtain the merged regions, and (4) segmenting and merging the color-mixing noisy superpixels in each of the merged regions, are applied to the initial cluster images sequentially. Finally, the optimized segmentation results are obtained. The proposed method is tested and compared with existing methods based on simulated and real mural images. The results show that the proposed method is effective and outperforms the existing methods.

The surface spectral reflectance of an object is the key factor for high-fidelity color reproduction and material analysis, and spectral acquisition is the basis of its applications. Based on the theoretical imaging model of a digital camera, the spectral reflectance of any pixels in the image can be obtained through spectral reconstruction technology. This technology can avoid the application limitations of spectral cameras in open scenarios and obtain high spatial resolution multispectral images. However, the current spectral reconstruction algorithms are sensitive to the exposure variant of the test images. That is, when the exposure of the test image is different from that of the training image, the reconstructed spectral curve of the test object will deviate from the real spectral to varying degrees, which will lead to the spectral data of the target object being accurately reconstructed. This article proposes an optimized method for spectral reconstruction based on data augmentation and attention mechanisms using the current deep learning-based spectral reconstruction framework. The proposed method is exposure invariant and will adapt to the open environment in which the light is easily changed and the illumination is non-uniform. Thus, the robustness and reconstruction accuracy of the spectral reconstruction model in practical applications are improved. The experiments show that the proposed method can accurately reconstruct the shape of the spectral reflectance curve of the test object under different test exposure levels. And the spectral reconstruction error of our method at different exposure levels is significantly lower than that of the existing methods, which verifies the proposed method’s effectiveness and superiority.

Combined with microfluidics, surface-enhanced Raman spectroscopy (SERS) exhibits huge application prospective in sensitive online detection. In current studies, the design and optimization of plasmonic enhanced structures in microfluidics for SERS detection could be an interesting challenge. In this work, hybrid plasmonic 2D microplates composed of Mxenes (Ti3C2Tx) microplates and in-situ synthesized Au nanoparticles (Au NPs) are fabricated in a microchannel for enhanced structures in SERS microfluidics. Benefiting from the 2D Mxenes microplates with complex distributions, the enhanced areas generated by Au NPs are quite enlarged in a microchannel, which exhibits high sensitivity in SERS detection at 10−10 M for Nile blue (NB) molecules in microfluidics. The mechanism of electromagnetic enhancement (EM) and chemical enhancement (CM) is analyzed. The experimental data indicate the ultrasonic times of Mxenes and the concentration of Au3+ play important roles in the sensitivity of SERS detection, which is confirmed by the simulated electric field distributions. Furthermore, a typical pesticide (thiram) at 100 ppm in water is detected on these SERS microfluidics with hybrid plasmonic enhanced structures, which demonstrates that our work not only strengthens the knowledge of plasmonics but also enlarges the application of SERS.

Abstract With high sensitivity at single molecule level, surface-enhanced Raman scattering (SERS) is considered as an ultrasensitive optical detection technology with broad application prospects in lots of fields. However, the complicated fabrication and unaffordable price of SERS substrate are still a roadblock on the way to be widely used in industry. In this work, the SERS spectra on a commercial laser engraved Teflon (PTFE) film with engraved microarray are investigated. The wettability of film surface modulated by laser engraving make the microarray have the ability to decrease the contact area on film surface while water evaporation. The SEM image of the engraved area points out the micro/nanostructures generated engraving process is crucial to its superhydrophobic property. The probing molecules (i.e., methylene blue and rhodamine6G) were utilized to investigate with the limit of detection (1 × 10−14 M). Furthermore, the biomolecule (bovine serum albumin) was used to demonstrate its benefits in biological applications. The measured intensities of Raman spectra on this PTFE with laser engraved microarray demonstrate its potential value for a SERS substrate. Our work on this simple, cheap SERS substrate with high sensitivity has a great commercial value and plenty of application in lots of fields.

Abstract Benefiting from the induced image charge on metal film, the light energy is confined on a film surface under metal nanoparticle dimer, which is called electromagnetic field redistribution. In this work, electromagnetic field distribution of metal nanoparticle monomer or dimer on graphene is investigated through finite-difference time-domain method. The results point out that the electromagnetic field (EM) redistribution occurs in this nanoparticle/graphene hybrid system at infrared region where light energy could also be confined on a monolayer graphene surface. Surface charge distribution was analyzed using finite element analysis, and surface-enhanced Raman spectrum (SERS) was utilized to verify this phenomenon. Furthermore, the data about dielectric nanoparticle on monolayer graphene demonstrate this EM redistribution is attributed to strong coupling between light-excited surface charge on monolayer graphene and graphene plasmon-induced image charge on dielectric nanoparticle surface. Our work extends the knowledge of monolayer graphene plasmon, which has a wide range of applications in monolayer graphene-related film.

We estimate the heat flux changes caused by the projected land transformation over the next 40 years across China to improve the understanding of the impacts of land dynamics on regional climate. We use the Weather Research and Forecasting (WRF) model to investigate these impacts in four representative land transformation zones, where reclamation, overgrazing, afforestation, and urbanization dominates the land use and land cover changes in each zone respectively. As indicated by the significant variance of albedo due to different land use and cover changes, different surface properties cause great spatial variance of the surface flux. From the simulation results, latent heat flux increases by 2 and 21 W/m2 in the reclamation and afforestation regions respectively. On the contrary, overgrazing and urban expansion results in decrease of latent heat flux by 5 and 36 W/m2 correspondingly. Urban expansion leads to an average increase of 40 W/m2 of sensible heat flux in the future 40 years, while reclamation, afforestation, as well as overgrazing result in the decrease of sensible heat flux. Results also show that reclamation and overgrazing lead to net radiation decrease by approximately 4 and 7 W/m2 respectively, however, afforestation and urbanization lead to net radiation increase by 6 and 3 W/m2 respectively. The simulated impacts of projected HLCCs on surface energy fluxes will inform sustainable land management and climate change mitigation.

In this article, we study oscillatory properties of solutions to neutral nonlinear impulsive hyperbolic partial differential equations with several delays. We establish sufficient conditions for oscillation of all solutions.

Hollow noble metal nanoparticles have excellent performance not only in surface catalysis but also in optics. In this work, the hollow Au–Ag alloy nanorices are fabricated by the galvanic replacement reaction. The dark-field spectrum points out that there is a big difference in the optical properties between the pure Ag nanorices and the hollow alloy nanorices that exhibit highly tunable localized surface plasmon resonances (LSPR) and that possess larger radiative damping, which is also indicated by the finite element method. Furthermore, the surface enhanced Raman scattering (SERS) and oxidation test indicate that hollow Au–Ag alloy nanorices show good anti-oxidation and have broad application prospects in surface-plasmon-related fields.

We introduce the fractional-order derivatives into an HIV infection model with nonlinear incidence and show that the established model in this paper possesses nonnegative solution, as desired in any population dynamics. We also deal with the stability of the infection-free equilibrium, the immune-absence equilibrium, and the immune-presence equilibrium. Numerical simulations are carried out to illustrate the results.

In this paper, we study oscillatory properties of solutions to nonlinear impulsive hyperbolic equations with several delays. Sufficient conditions for oscillations of the solutions are established.

A diffusive predator-prey system with disease in predator species and no-flux boundary condition is considered. Sufficient conditions which ensure persistence of the system are obtained. Conditions of disease-free ecosystem are also studied. Furthermore, sufficient conditions for global asymptotic stability of the unique positive equilibrium and disease-free equilibrium of the system are derived using the approach of Lyapunov function.

An agroecological zone (AEZ) is a land resource mapping unit, defined in terms of climate, landform, and soils, and has a specific range of potentials and constraints for cropping (FAO, 1996). The shifting patterns of AEZs in China driven by future climatic changes were assessed by applying the agroecological zoning methodology proposed by International Institute for Applied Systems Analysis (IIASA) and Food and Agriculture Organization of the United Nations (FAO) in this study. A data processing scheme was proposed in this study to reduce systematic errors in projected climate data using observed data from meteorological stations. AEZs in China of each of the four periods: 2011–2020, 2021–2030, 2031–2040, and 2041–2050 were drawn. It is found that the future climate change will lead to significant local changes of AEZs in China and the overall pattern of AEZs in China is stable. The shifting patterns of AEZs will be characterized by northward expansion of humid AEZs to subhumid AEZs in south China, eastward expansion of arid AEZs to dry and moist semiarid AEZs in north China, and southward expansion of dry semiarid AEZs to arid AEZs in southwest China.

The afforestation is one of the most noticeable human activities that affect the climate through influencing not only the carbon sink but also the thermal properties of the land surface. This research accessed the potential effects of artificial vegetation change on the regional climate in Jiangxi Province, China. Based on simulation with the Weather Research and Forecasting (WRF) model, a comparative analysis was carried out on the future temperature and precipitation under four hypothetical vegetation cover scenarios. The simulation results indicated that the vegetation change would have significant effects on the regional climate. The simulated effects of annual average temperature showed a decreasing order: evergreen broadleaf > evergreen needleleaf > deciduous needleleaf > deciduous broadleaf, and the effects of annual average precipitation of the evergreen forests would be bigger than those of the deciduous forests. The deciduous forests play a positive role in decreasing the annual average temperature, while the evergreen forests promote the annual average temperature rise. Besides, the expansion of deciduous forests may result in severe drought in the summer in Jiangxi Province. These conclusions are of important policy implication to the future afforestation in Jiangxi Province, China, and other regions of the world.

In this paper, evidences for influences of future urban expansion on regional climate in the Northeast megalopolis, USA, are presented. The model-based analysis shows that future urban expansion will significantly result in regional climate change. An average annual temperature increase ranging from 2°C to 5°C in new urban area and an average annual temperature decrease ranging from 0.40°C to 1.20°C in the south of the megalopolis will be caused by future urban expansion. The average annual precipitation of the simulation area will decrease due to future urban expansion by 5.75 mm, 7.10 mm, and 8.35 mm in the periods of 2010–2020, 2040–2050, and 2090–2100, respectively. The warming effect of future urban expansion in original and new urban area and drought effects in nonurban area will be more serious in summer than in winter. A cooling effect will turn up in original urban area in winter. This research further shows that a study at the scale of megalopolis helps to understand the integrated effect of combination and interaction of multiple cities and their surrounding areas which may crucially determine regional climate pattern and should be highly valued in the future.